Optimization of dynamic properties for laminated multiphase nanocomposite sandwich conical shell in thermal and magnetic conditions

This paper extends an optimization procedure to obtain the optimal dynamic properties of laminated sandwich multiphase nanocomposite truncated conical shell under magneto-hygro-thermal conditions. Based on principle of Hamilton, the equations of motion are obtained and solved by differential quadrature method and Bolotin's methods for obtaining the dynamic stability region. Based on particle swarm optimization and harmony search algorithms, a novel hybrid optimization method basis HS and PSO is proposed to enhance the performance and convergence of optimum dynamic conditions in this problem. By applying the hybrid optimization algorithm namely as HS-PSO, the volume percent of CNT and carbon fiber, number of laminas, cone semi vertex angle and moisture changes are optimized and the effects of magnetic field and temperature are shown on the dynamic stability of system. The result illustrates that proposed PSO-HS method with same conditions by other optimization methods as harmony memory size (number of particles) of 5 and total iterations of 100 shows the superior convergence performance compare to HS and PSO algorithms.

Automated summary

This study presents an optimization procedure to obtain the optimal dynamic properties of laminated sandwich multiphase nanocomposite truncated conical shell under magneto-hygro-thermal conditions. A novel hybrid optimization method based on particle swarm optimization and harmony search algorithms is proposed to enhance the performance and convergence of optimum dynamic conditions. The hybrid optimization algorithm, HS-PSO, shows superior convergence performance compared to other optimization methods.